A novel stacked memristor architecture performs Euclidean distance calculations directly within memory, enabling ...
An analog in-memory compute chip claims to solve the power/performance conundrum facing artificial intelligence (AI) inference applications by facilitating energy efficiency and cost reductions ...
[CONTRIBUTED THOUGHT PIECE] Generative AI is unlocking incredible business opportunities for efficiency, but we still face a formidable challenge undermining widespread adoption: the exorbitant cost ...
While NVIDIA includes its CPU and RAM in its super-speed GPU fabric, AMD may have done something else altogether with its ...
Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
"Firstly, traditional sorting hardware involves extensive comparison and select logic, conditional branching, or swap operations, featuring irregular control flow that fundamentally differs from the ...
The biggest challenge posed by AI training is in moving the massive datasets between the memory and processor.
SUNNYVALE, Calif.--(BUSINESS WIRE)--ANAFLASH, a Silicon Valley-based pioneer in low power edge computing, has acquired Legato Logic’s time-based compute-in-memory technologies and its industry ...
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AI efficiency advances with spintronic memory chip that combines storage and processing
To make accurate predictions and reliably complete desired tasks, most artificial intelligence (AI) systems need to rapidly analyze large amounts of data. This currently entails the transfer of data ...
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